This invention relates to a pattern matching system for comparing two patterns each given as a series of feature vectors like a voice pattern.
A pattern matching process wherein an incoming unknown pattern is compared with a plurality of dictionary patterns being previously registered and the one dictionary pattern with the highest similarity is determined as the incoming unknown pattern has been generally applied as an available method for pattern recognition.
It is essential for the pattern matching process to cope with variations, such as changes in speaking speed in a voice pattern. A time normalizing matching process (DP process) employing a dynamic programming process such as disclosed, for example, in U.S. Pat. Nos. 4,059,725 and 4,326,101 will be exceedingly effective. However, in the matching process, since a pattern to be matched should be expressed by a time series of feature vectors sampled at a predetermined constant period, a storage requirement for storing the feature vectors will inevitably increase to store a long voice pattern, and the amount of processing required will also increase. To overcome such problems, a compressed DP process is utilized wherein representative vectors are sampled at nonuniform sampling periods where there is present a stationary part in a pattern, like a vowel part of the voice pattern. Applying the DP process to a series of the representative vectors is proposed in the U.S. patent application Ser. No. 353,293 filed on Mar. 1, 1982.
However, in the compressed DP process, a data quantity is not compressed at a transition part in which the pattern changes, and the interval between a representative vector and succeeding representative vector is approximated retangularly, therefore an approximation error from the original pattern will be unavoidable. Then, by approximating the original pattern in a connection of straight line segments, i.e., piecewise straight line segment and extracting the connecting point as a representative vector, the data is compressed even at the transition part in which the pattern changes, and the approximation error from the original pattern is minimized, thus realizing a high precision of matching with less storage and computation requirements. In this case, however, the extracted representative vector has not already represented a section according to an original pattern, but a segment connecting the two adjacent representative vectors represents a section of the original pattern. In this respect, therefore, the conventional compressed DP matching process using the distance between the representative vector of a pattern A and the representative vector of a pattern B for matching of the two patterns A and B is not applicable when representative vectors are given as connecting points of the line segment.